Yi-Chiao Wu
Artificial Intelligence · 2016–2023
A researcher in the Science corpus: 9 papers; trusts 156 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 166 citations into it; #9,484 of 35,345 by trust here, #8,810 by citations
- Signal Processing — 138 citations into it; #3,964 of 7,572 by trust here, #1,629 by citations
- Speech & Audio — 94 citations into it; #651 of 1,076 by trust here, #559 by citations
- Computer Vision and Pattern Recognition — 58 citations into it; #12,919 of 21,575 by trust here, #10,334 by citations
- Natural Language Processing — 44 citations into it
- Generative Models — 34 citations into it; #1,177 of 1,956 by trust here, #1,163 by citations
- Representation & Self-Supervised Learning — 22 citations into it
- Model Architectures — 13 citations into it
Whom Yi-Chiao Wu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Aäron van den Oord
- Masanori Morise
- Ilya Sutskever
- Alex Graves
- Oriol Vinyals
- Yann LeCun
Who trusts Yi-Chiao Wu overall
- Hirokazu Kameoka
- Berrak Sisman
- Seyed Hamidreza Mohammadi
- Takuhiro Kaneko
- Junichi Yamagishi
- Zhichao Huang
- Sercan Ö. Arik
- Xin Eric Wang
- Chin-Cheng Hsu
- Wei-Ning Hsu
Papers from Yi-Chiao Wu's perspective
Ordered by how strongly the researchers Yi-Chiao Wu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Voice Conversion from Unaligned Corpora Using Variational Autoencoding Wasserstein Generative Adversarial Networks (2017) — 326 citations
- Voice conversion from non-parallel corpora using variational auto-encoder (2016) — 319 citations
- Audiodec: An Open-Source Streaming High-Fidelity Neural Audio Codec (2023) — 139 citations
- Locally Linear Embedding for Exemplar-Based Spectral Conversion (2016) — 37 citations
- Pretraining Techniques for Sequence-to-Sequence Voice Conversion (2020) — 49 citations
- Unified Source-Filter GAN: Unified Source-filter Network Based On Factorization of Quasi-Periodic Parallel WaveGAN (2021) — 13 citations
- The AS-NU System for the M2VoC Challenge (2021)
- Quasi-Periodic Parallel WaveGAN Vocoder: A Non-autoregressive Pitch-dependent Dilated Convolution Model for Parametric Speech Generation (2020) — 4 citations
- Cyclic Spectral Modeling for Unsupervised Unit Discovery into Voice Conversion with Excitation and Waveform Modeling (2020) — 8 citations